SPSS software

Principal component analysis (PCA) of the soil physico-chemical or the antibiotic resistance data set was performed with the SPSS software. Before PCA, the row MPN values were log-ratio transformed (ter Braak and Smilauer 1998) each MPN was logio -transformed, then, divided by sum of the 16 log-transformed values. Simple linear regression analysis between scores on PCs based on the antibiotic resistance profiles and the soil physico-chemical characteristics was also performed using the SPSS software. To find the PCs that significantly explain variation of SFI or SEF value, multiple regression analysis between SFI or SEF values and PC scores was also performed using the SPSS software. The stepwise method at the default criteria (p=0.05 for inclusion and 0.10 for removal) was chosen. 

All data were analyzed as paired samples using the Wilcoxon test. For all calculations, SPSS software was used. 

Descriptive statistics (number of observations (n), mean, standard deviation, coefficient of variation in percent (CV %) or median and range) were calculated for each parameter. Statistical tests using SPSS software were as follows ... 

Data processing parameters Tire deuterium NMR peak area was normalized to peak area percentage. Principal component analysis (PCA) was conducted using SPSS software package. The final results were presented as a two dimensional PCA plot using the first two principal components. 

The interviews were recorded and transcribed. Qualitative data from the interviews were analysed with ATLAS.ti software that allows coding and structuring interview material for easier analysis. Quantitative information related to the 620 disposed clothing items was coded in Excel and finally analysed with SPSS software. 

The MULTILOG 7 software program (Thissen 1991) was used to fit a graded IRT response model (Samejima 1969) estimating item discrimination and location parameters (Embretson and Reise 2000) for each HSOPSC item. SPSS software (PASW 18.0) was used to calculate correlations between mean scale scores and corresponding IRT scale scores. 

Through the above steps, the commercial ages of enterprises in the Xishan Ecological Industrial Park from the year of 2002 to 2010 were obtained by using the SPSS software. The calculation results are shown in Table 1. 

SPSS software version 17 was used to analyze the data and to find the best device that reproduces the closest skin color. Normal distribution of data and homogeneity of variance were tested and approved so that one way ANOVA and independent t- test can be applied to compare the skin color based on ethnic groups and gender for each device. 

A descriptive statistics was used to study the features of the entire signal. The Wilcoxon Rank Sum was used to examine the differences between the two postures. The significant level was set at p<0.05. The data was analyzed using the Statistical Package for the Social Sciences (SPSS) software, version 14.0. 

After irradiation was performed, non- irradiated and irradiated samples of the blood parameter, Hematocrit, and the beam parameter,Flux peak, were compared. The paired test was used to determine the differences between the controlled samples and irradiated samples. A two- factor analysis were further conducted to examine the differences in the samples according to the age, gender of patients. The SPSS software version 12 was utilized to perform statistical calculations and analyses of the data. 

The values of bio-impedance measured by both the sensors from ten subjects were compared by t-distribution using the SPSS software. The values of bio-impedance measured by an Ag/AgCl electrode were 7.934 9.004 2 and those of bio-impedance measured by the strip-type conductive fabric sensor were 15.001 12.336 2. 

Regression analysis, Spearman s correlations and the Mann-Whitney Test were computed using SPSS software REF Testing for homogeneity of variance was done using either the F-test or the Burr-Foster Q-Test as previously described. Data were transformed with either the square-root or logy transformations. Significance was considered at P<0.05. 

Statistical analysis. Results were given as means SEM. Significant differences were detected by one-way ANOVA followed by Student s t test using the SPSS software (SPSS Inc. Chicago, IL, USA). P<0.05 was considered to denote significance. 

One-way analysis of variance (ANOVA) to test the significant effect of the degrading impact on each soil characteristic was performed using the computer software, SPSS 10.0.5J (SPSS Japan Inc., Tokyo). The Dunnett T3 test was chosen as the post-hoc test. 

The data obtained was analyzed using SPSS-9.0 software. Any differences with a significance level p<0.05 were considered valid. To assess the validity of the differences and correlation, non-parametric tests were used as indicated vide infra). The data are displayed as mean SE. 

Selected characteristics were compared between cases and controls by using test. The analyses of data were performed using the computer software SPSS for Windows version 11.5. Max type 1 error was accept as 0.05. Binary logistic regression was performed to calculate the odds ratios (ORs), and 95% confidence intervals (Cls) to assess the risk of breast cancer. 

Experimental data and calculated data for the photodegradation of chlo-rophenols were compared using multivariate analysis and SPSS statistical software. A linear expression was developed using the independent variables Kow and ores and the dependent variable log k/kQ. Calculated values for log k/k0 were obtained from the following linear equation ... 

The raw and the standardized coordinates are calculated both manually and using software [STATISTICA, 1995], As in most cases where the reader of publications wants to reproduce the results, surprisingly we get a different result. In our case this is because most software (SPSS, STATISTICA,. ..) calculates a constant along with the raw coefficients. At the same time this demonstrates that there are several ways of finding discriminant functions. So, in some instances it may be convenient to use so-called elementary discriminant functions [AHRENS and LAUTER, 1981] or to try quadratic discrimination (see [FAHRMEIR and HAMERLE, 1984]). 

SPSS www.sas. c om/technologies/analytics/stadstics/stat/) IBM A computer program used for data mining and statistical analysis (http // www-01. ibm.com/software/ analytics/spss/)... 

Programs such as dBASE II, III PLUS, or IV, and LOTUS allow the user to work easily with databases and perform the calculations that can be summarized in tabular form, respectively. It should be noted that it is also possible to connect these programs to other software. For instance, to use the SPSS/PC + (ref. 6), one can enter the data first into a spreadsheet and perform corrections in this spreadsheet. Another possibility is to use dBASE as a receptacle of knowledge, which can be changed by the user, and connect this to an expert system in which the knowledge that cannot be changed by the end user is embedded. 

One of die difficulties is to decide what software to employ in order to analyse the data. This book is not restrictive and you can use any approach you like. Some readers like to program their own mediods, for example in C or Visual Basic. Others may like to use a statistical packages such as SAS or SPSS. Some groups use ready packaged chemometrics software such as Pirouette, Simca, Unscrambler and several others on the market. One problem widi using packages is that they are often very... 

Most traditional approaches to classification in science are called discriminant analysis and are often also called forms of hard modelling . The majority of statistically based software packages such as SAS, BMDP and SPSS contain substantial numbers of procedures, referred to by various names such as linear (or Fisher) discriminant analysis and canonical variates analysis. There is a substantial statistical literature in this area. 

The statistical software systems used for analysis of clitucal trial data can range from custom programs for specific statistical techniques to COTS packages. Such packages (e g, the SAS system, SPSS, S-Plus) provide the user with a library of statistical procedures (e.g., analysis of variance, regression, generahzed linear modelling, nonparametric methods) which can be accessed either by... 

To elegantly present the results of a Conjoint Analysis, the values derived from respondents can be converted to a market simulator what-if tool). Some software programs worthy of investigation are SAS, SPSS, and Sawtooth. 

Means and standard deviations (SD) were calculated with SPSS (Version 11.5.1, SPSS Inc., Chicago, IL, USA) statistical software. SPSS was used to verify significant differences between treatments by one-way analysis of variance (ANOVA) followed by least significant difference test (LSD) at p < 0.05 to identify differences among groups. 

Collected data were subjected to descriptive statistics, analysis of variance, log-linear regression, and trend analysis using STATISTICA, SPSS ver. 10 and MINITAB Ver. 14 statistical software. 

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